Micro-Star International Co., Ltd. Prestige 16 AI Evo B2HMG
Geekbench AI Score
2969
Single Precision Score
7946
Half Precision Score
11917
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | July 01 2025 09:12 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. Prestige 16 AI Evo B2HMG |
| Motherboard | Micro-Star International Co., Ltd. MS-15A1 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285H |
| Topology | 1 Processor, 16 Cores |
| Identifier | GenuineIntel Family 6 Model 197 Stepping 2 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1645
306.0 IPS |
|
|
Image Classification (HP)
|
100% |
5337
992.5 IPS |
|
|
Image Classification (Q)
|
100% |
7316
1.36 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2125
34.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2663
43.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
3721
60.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
4424
5.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
32826
38.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
70106
82.1 IPS |
|
|
Object Detection (SP)
|
100% |
1521
120.7 IPS |
|
|
Object Detection (HP)
|
100% |
5266
417.7 IPS |
|
|
Object Detection (Q)
|
87% |
7540
605.2 IPS |
|
|
Face Detection (SP)
|
100% |
4714
56.0 IPS |
|
|
Face Detection (HP)
|
100% |
14724
174.9 IPS |
|
|
Face Detection (Q)
|
100% |
20425
242.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
4800
37.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
18865
145.3 IPS |
|
|
Depth Estimation (Q)
|
88% |
32732
254.7 IPS |
|
|
Style Transfer (SP)
|
100% |
12819
16.5 IPS |
|
|
Style Transfer (HP)
|
100% |
46747
60.1 IPS |
|
|
Style Transfer (Q)
|
98% |
77797
100.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2209
81.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
12022
443.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
18018
667.3 IPS |
|
|
Text Classification (SP)
|
100% |
1715
2.29 KIPS |
|
|
Text Classification (HP)
|
100% |
926
1.24 KIPS |
|
|
Text Classification (Q)
|
92% |
1423
1.91 KIPS |
|
|
Machine Translation (SP)
|
100% |
2064
35.6 IPS |
|
|
Machine Translation (HP)
|
100% |
2828
48.7 IPS |
|
|
Machine Translation (Q)
|
100% |
3011
51.9 IPS |
